Analysis of proportional mean residual life model with latent variables

doi:10.1002/sim.7174

CSpace > 应用数学研究所

	Analysis of proportional mean residual life model with latent variables
	He, Haijin 1; Cai, Jingheng 2; Song, Xinyuan 3,4; Sun, Liuquan5
	2017-02-01
发表期刊	STATISTICS IN MEDICINE
ISSN	0277-6715
卷号	36 期号:5 页码:813-826
摘要	End-stage renal disease (ESRD) is one of the most serious diabetes complications. Numerous studies have been devoted to revealing the risk factors of the onset time of ESRD. In this article, we propose a proportional mean residual life (MRL) model with latent variables to assess the effects of observed and latent risk factors on the MRL function of ESRD in a cohort of Chinese type 2 diabetic patients. The proposed model generalizes the conventional proportional MRL model to accommodate the latent risk factor that cannot be measured by a single observed variable. We employ a factor analysis model to characterize the latent risk factors via multiple observed variables. We develop a borrow-strength estimation procedure, which incorporates the expectation-maximization algorithm and an extended estimating equation approach. The asymptotic properties of the proposed estimators are established. Simulation shows that the performance of the proposed methodology is satisfactory. The application to the study of type 2 diabetes reveals insights into the prevention of ESRD. Copyright (C) 2016 John Wiley & Sons, Ltd.
关键词	borrow-strength estimation extended estimating equations factor analysis latent variables mean residual life function proportional model
DOI	10.1002/sim.7174
语种	英语
资助项目	Research Grant Council of the Hong Kong Special Administration Region[14601115] ; Research Grant Council of the Hong Kong Special Administration Region[14305014] ; Chinese University of Hong Kong ; National Natural Science Foundation of China[11471277] ; National Natural Science Foundation of China[11231010] ; National Natural Science Foundation of China[11171330] ; Key Laboratory of RCSDS, CAS[2008DP173182]
WOS研究方向	Mathematical & Computational Biology ; Public, Environmental & Occupational Health ; Medical Informatics ; Research & Experimental Medicine ; Mathematics
WOS类目	Mathematical & Computational Biology ; Public, Environmental & Occupational Health ; Medical Informatics ; Medicine, Research & Experimental ; Statistics & Probability
WOS记录号	WOS:000393303200007
出版者	WILEY-BLACKWELL
引用统计
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/24689
专题	应用数学研究所
通讯作者	Song, Xinyuan
作者单位	1.Shenzhen Univ, Coll Math & Comp Sci, Shenzhen, Peoples R China 2.Sun Yat Sen Univ, Dept Stat, Guangzhou, Guangdong, Peoples R China 3.Chinese Univ Hong Kong, Shenzhen Res Inst, Hong Kong, Hong Kong, Peoples R China 4.Chinese Univ Hong Kong, Dept Stat, Hong Kong, Hong Kong, Peoples R China 5.Chinese Acad Sci, Acad Math & Syst Sci, Inst Appl Math, Beijing, Peoples R China
推荐引用方式 GB/T 7714	He, Haijin,Cai, Jingheng,Song, Xinyuan,et al. Analysis of proportional mean residual life model with latent variables[J]. STATISTICS IN MEDICINE,2017,36(5):813-826.
APA	He, Haijin,Cai, Jingheng,Song, Xinyuan,&Sun, Liuquan.(2017).Analysis of proportional mean residual life model with latent variables.STATISTICS IN MEDICINE,36(5),813-826.
MLA	He, Haijin,et al."Analysis of proportional mean residual life model with latent variables".STATISTICS IN MEDICINE 36.5(2017):813-826.